1. LFMM

1.1 Individual sampling

1.1.1 Summary plots

K

walk(K_plots, grid.arrange)

TPRCOMBO

walk(TPR_plots, grid.arrange)

FDRCOMBO

walk(FDR_plots, grid.arrange)

### TOTALN

walk(TOTALN_plots, grid.arrange)

1.1.2 Model summaries

lfmm_ind <- 
  lfmm_ind %>% 
  filter(padj == "fdr") %>%
  filter(sig == 0.05) %>%
  filter(method == "ridge") %>%
  filter(K_selection == "tracy.widom")
run_lmer(lfmm_ind, "TPRCOMBO", filepath = here(p4path, "LFMM_individual_TPR.csv"))
Contrast Estimate SE Z ratio p
envgeo - grid −0.0014 0.0023 −0.5884 0.9356357
envgeo - rand 0.0030 0.0023 1.2888 0.5700741
envgeo - trans*** 0.0176 0.0023 7.5786 2.3 × 10−13***
grid - rand 0.0044 0.0023 1.8772 0.2378691
grid - trans*** 0.0190 0.0023 8.1670 4.9 × 10−14***
rand - trans*** 0.0146 0.0023 6.2899 1.9 × 10−9***
*** p < 0.001
run_lmer(lfmm_ind, "FDRCOMBO", filepath = here(p4path, "LFMM_individual_FDR.csv"))
Contrast Estimate SE Z ratio p
envgeo - grid 0.0074 0.0095 0.7829 0.86225851
envgeo - rand*** −0.0246 0.0095 −2.5990 0.04614817***
envgeo - trans** −0.0760 0.0095 −8.0269 5.9 × 10−14**
grid - rand* −0.0320 0.0095 −3.3819 4.0 × 10−3*
grid - trans** −0.0834 0.0095 −8.8098 3.0 × 10−14**
rand - trans** −0.0514 0.0095 −5.4278 3.4 × 10−7**
*** p < 0.05
** p < 0.001
* p < 0.01
run_lmer(lfmm_ind, "TOTALN", filepath = here(p4path, "LFMM_individual_TOTALN.csv"))
Contrast Estimate SE Z ratio p
envgeo - grid*** 0.2065 0.0707 2.9201 0.01837934***
envgeo - rand 0.0656 0.0707 0.9279 0.78986890
envgeo - trans** −0.7362 0.0707 −10.4098 4.3 × 10−14**
grid - rand −0.1409 0.0707 −1.9921 0.19087871
grid - trans** −0.9427 0.0707 −13.3299 0.0**
rand - trans** −0.8018 0.0707 −11.3378 0.0**
*** p < 0.05
** p < 0.001

1.1.3 Megaplots

MEGAPLOT(lfmm_ind, "K.1", colpal = "turbo")

MEGAPLOT(lfmm_ind, "TPRCOMBO", colpal = "plasma")

MEGAPLOT(lfmm_ind, "FDRCOMBO", colpal = "viridis", direction = -1)

MEGAPLOT(lfmm_ind, "TOTALN", colpal = "viridis")

### 1.1.4 Latent factor versus sample number test

walk(K_plots, grid.arrange)

walk(TPR_plots, grid.arrange)

walk(FDR_plots, grid.arrange)

walk(TOTALN_plots, grid.arrange)

1.2 Site sampling

1.2.1 Summary plots

K

walk(K_plots, grid.arrange)

TPRCOMBO

walk(TPR_plots, grid.arrange)

FDRCOMBO

walk(FDR_plots, grid.arrange)

TOTALN

walk(TOTALN_plots, grid.arrange)

1.1.2 Model summaries

lfmm_site <- 
  lfmm_site %>% 
  filter(padj == "fdr") %>%
  filter(sig == 0.05) %>%
  filter(method == "ridge") %>%
  filter(K_selection == "tracy.widom")
run_lmer(lfmm_site, "TPRCOMBO", filepath = here(p4path, "LFMM_site_TPR.csv"))
Contrast Estimate SE Z ratio p
envgeo - equi 0.0042 0.0023 1.8455 0.15493454
envgeo - rand*** 0.0091 0.0023 4.0177 1.7 × 10−4***
equi - rand 0.0049 0.0023 2.1723 0.07598666
*** p < 0.001
run_lmer(lfmm_site, "FDRCOMBO", filepath = here(p4path, "LFMM_site_FDR.csv"))
Contrast Estimate SE Z ratio p
envgeo - equi −0.0057 0.0046 −1.2394 0.4298770
envgeo - rand −0.0020 0.0046 −0.4349 0.9010300
equi - rand 0.0037 0.0046 0.8046 0.7001826
run_lmer(lfmm_site, "TOTALN", filepath = here(p4path, "LFMM_site_TOTALN.csv"))
Contrast Estimate SE Z ratio p
envgeo - equi*** 6.7684 2.1833 3.1001 5.5 × 10−3***
envgeo - rand 4.3663 2.1833 1.9999 0.1122041
equi - rand −2.4021 2.1833 −1.1002 0.5139103
*** p < 0.01

1.2.3 Megaplots

MEGAPLOT(lfmm_site, "K.1", colpal = "turbo")

MEGAPLOT(lfmm_site, "TPRCOMBO", colpal = "plasma")

MEGAPLOT(lfmm_site, "FDRCOMBO", colpal = "viridis", direction = -1)

MEGAPLOT(lfmm_site, "TOTALN", colpal = "viridis")

### 1.2.4 Latent factor versus sample number test

walk(K_plots, grid.arrange)

walk(TPR_plots, grid.arrange)

walk(FDR_plots, grid.arrange)

walk(TOTALN_plots, grid.arrange) 

2. RDA

2.1 Individual sampling

2.1.1 Summary plots

rda_ind <- format_rda(here(p3path, "rda_indsampling_results.csv"))
rda_ind_tidy <- 
  rda_ind %>%
  filter(padj == "fdr") %>%
  filter(sig == 0.05) %>%
  group_by(correctPC) %>%
  group_split()
walk(TPR_plots, grid.arrange)

walk(FDR_plots, grid.arrange)

2.1.2 Model summaries

rda_ind <- 
  rda_ind %>% 
  filter(padj == "fdr") %>%
  filter(sig == 0.05) %>%
  filter(correctPC == "FALSE") 
run_lmer(rda_ind, "TPRCOMBO", filepath = here(p4path, "RDA_individual_TPR.csv"))
Contrast Estimate SE Z ratio p
envgeo - grid 0.0004 0.0017 0.2367 0.9953359
envgeo - rand 0.0029 0.0017 1.7358 0.3050510
envgeo - trans*** 0.0110 0.0017 6.6472 1.8 × 10−10***
grid - rand 0.0025 0.0017 1.4991 0.4380159
grid - trans*** 0.0106 0.0017 6.4105 8.7 × 10−10***
rand - trans*** 0.0081 0.0017 4.9114 5.4 × 10−6***
*** p < 0.001
run_lmer(rda_ind, "FDRCOMBO", filepath = here(p4path, "RDA_individual_FDR.csv"))
Contrast Estimate SE Z ratio p
envgeo - grid −0.0010 0.0029 −0.3565 0.98447702
envgeo - rand 0.0017 0.0029 0.6110 0.92862133
envgeo - trans*** 0.0085 0.0029 2.9768 0.01543605***
grid - rand 0.0028 0.0029 0.9675 0.76794265
grid - trans** 0.0095 0.0029 3.3333 4.8 × 10−3**
rand - trans 0.0067 0.0029 2.3658 0.08376928
*** p < 0.05
** p < 0.01
run_lmer(rda_ind, "TOTALN", filepath = here(p4path, "RDA_individual_TOTALN.csv"))
Contrast Estimate SE Z ratio p
envgeo - grid 0.0018 0.0247 0.0739 0.9998551
envgeo - rand 0.0406 0.0247 1.6478 0.3517771
envgeo - trans*** 0.1505 0.0247 6.1052 6.2 × 10−9***
grid - rand 0.0388 0.0247 1.5738 0.3936324
grid - trans*** 0.1487 0.0247 6.0313 9.8 × 10−9***
rand - trans*** 0.1099 0.0247 4.4574 4.9 × 10−5***
*** p < 0.001

1.1.3 Megaplots

MEGAPLOT(rda_ind, "TPRCOMBO", colpal = "plasma")

MEGAPLOT(rda_ind, "FDRCOMBO", colpal = "viridis", direction = -1)

MEGAPLOT(rda_ind, "TOTALN", colpal = "viridis")

2.2 Site sampling

2.2.1 Summary plots

rda_site <- format_rda(here(p3path, "rda_sitesampling_results.csv")) 
rda_site_tidy <- 
  rda_site %>%
  filter(padj == "fdr") %>%
  filter(sig == 0.05) %>%
  group_by(correctPC) %>%
  group_split()
walk(TPR_plots, grid.arrange)

walk(FDR_plots, grid.arrange)

walk(TOTALN_plots, grid.arrange)

2.2.2 Model summaries

rda_site <- 
  rda_site %>% 
  filter(padj == "fdr") %>%
  filter(sig == 0.05) %>%
  filter(correctPC == "FALSE") 
run_lmer(rda_site, "TPRCOMBO", filepath = here(p4path, "RDA_site_TPR.csv"))
Contrast Estimate SE Z ratio p
envgeo - equi −0.0005 0.0016 −0.2956 0.9529805
envgeo - rand*** 0.0076 0.0016 4.6756 8.7 × 10−6***
equi - rand*** 0.0080 0.0016 4.9712 2.0 × 10−6***
*** p < 0.001
run_lmer(rda_site, "FDRCOMBO", filepath = here(p4path, "RDA_site_FDR.csv"))
Contrast Estimate SE Z ratio p
envgeo - equi*** 0.0085 0.0025 3.3981 2.0 × 10−3***
envgeo - rand** 0.0123 0.0025 4.9457 2.3 × 10−6**
equi - rand 0.0039 0.0025 1.5476 0.2687622
*** p < 0.01
** p < 0.001
run_lmer(rda_site, "TOTALN", filepath = here(p4path, "RDA_site_TOTALN.csv"))
Contrast Estimate SE Z ratio p
envgeo - equi 0.0288 0.0207 1.3945 0.3437613
envgeo - rand*** 0.1160 0.0207 5.6115 6.0 × 10−8***
equi - rand*** 0.0872 0.0207 4.2171 7.3 × 10−5***
*** p < 0.001

2.2.3 Megaplots

MEGAPLOT(rda_site, "TPRCOMBO", colpal = "plasma")

MEGAPLOT(rda_site, "FDRCOMBO", colpal = "viridis", direction = -1)

MEGAPLOT(rda_site, "TOTALN", colpal = "viridis")